Principal Engineer

Principal Ai Forward Deployed EngineerOne of the best-known names in cruising, Princess is the world's leading international premium cruise line and tour company, carrying millions of guests each year to hundreds of destinations around the globe. We give our guests the Medallion Class experience others simply can't. The Love Boat promises something for everyone.We are looking to hire a Principal AI Forward Deployed Engineer. The Principal AI Forward Deployed Engineer is embedded directly with business units across the organization to quickly prototype, deploy, customize, and operationalize AI solutions that solve critical business problems. This role bridges the gap between the AI/Data team and the business—translating ambiguous challenges into working AI applications that deliver measurable value.This is a full-stack engineering role with deep backend expertise. You will design and build production-grade applications, APIs, and data pipelines that bring AI capabilities to life. Proficiency in modern application development, containerization, orchestration, and event-driven architectures is essential.Unlike traditional engineering roles, the Principal AI Forward Deployed Engineer operates at the intersection of technical execution and business problem-solving. You will work side-by-side with stakeholders in Guest Services, Revenue Management, Operations, Food & Beverage, and other functions to rapidly prototype, deploy, and iterate on AI solutions in real-world environments—including shipboard systems.This role requires a builder's mindset: someone who can scope a vague problem, architect a robust solution, write production-grade code, and ship it fast. You will bring field insights back to the core AI team, identifying reusable patterns and influencing the product roadmap based on what you learn in the field.Here's a summary of what Princess is looking for in a Principal AI Forward Deployed Engineer. Is this you?Responsibilities:AI Application Development & Deployment: Architect, build, and deploy enterprise-grade AI-powered applications using modern backend technologies (Python, Node.js, FastAPI, Express). Design and implement robust APIs and microservices architectures that integrate AI/ML models—including LLMs and agentic systems—with business systems at scale. Lead containerization strategies using Docker and manage complex deployments via Kubernetes (EKS/ECS) with a focus on reliability, scalability, and performance. Design and implement event-driven architectures using Kafka or similar streaming platforms for real-time data processing and AI inference. Take full ownership of end-to-end delivery from technical scoping and architecture design through production deployment, monitoring, optimization, and ongoing operational excellence.Rapid Prototyping & Problem Discovery: Deconstruct ambiguous, complex business problems into actionable AI solutions by deeply understanding operational context, system constraints, and stakeholder priorities. Rapidly build proof-of-concept applications using appropriate technology stacks to validate approaches and demonstrate business value. Architect scalable, production-ready solutions that account for performance, reliability, security, and maintainability from inception. Lead iterative development cycles based on user feedback, refining solutions until they deliver measurable, quantifiable business impact. Serve as a trusted advisor to business units on what is technically feasible and strategically valuable.Stakeholder Engagement & Technical Translation: Serve as the senior technical point of contact and trusted advisor for business stakeholders during AI deployments. Communicate complex technical concepts—including architecture decisions, trade-offs, risks, and recommendations—to executive leadership and non-technical audiences with clarity and confidence. Lead cross-functional collaboration with data scientists, data engineers, platform teams, infrastructure teams, microservice teams, security, privacy, and product managers to ensure solutions meet rigorous technical standards and business objectives. Build and maintain strong relationships with business partners through consistent delivery, transparent communication, and a demonstrated commitment to their success.Field Insights & Platform Feedback: Champion continuous improvement by bringing strategic learnings from field deployments back to the core AI/Data and Platform teams. Identify opportunities to improve tools, infrastructure, and reusable components that benefit the broader organization. Author and maintain comprehensive documentation including solution architectures, design patterns, and operational runbooks that enable knowledge transfer and accelerate future deployments. Proactively identify gaps in platform capabilities (CI/CD, observability, infrastructure, developer experience) and advocate for improvements with supporting business justification. Define and elevate engineering standards and best practices across the AI organization, mentor junior and mid-level engineers on these standards.Knowledge & Skills:Scope: The Senior Principal AI Forward Deployed Engineer operates as a technical leader across multiple business units—including Strategy & Analytics, Finance, Guest Services, Revenue Management, Operations, Marketing, and beyond—embedding directly with teams to architect and deploy enterprise-grade AI solutions in both shoreside and shipboard environments. This role commands the full technology stack, from backend application development (Python, Node.js, APIs, microservices) to infrastructure (Docker, Kubernetes, Kafka) and advanced AI/ML integration including LLMs and agentic systems. The incumbent serves as the primary technical authority during AI deployments, working cross-functionally with data scientists, data engineers, platform teams, infrastructure teams, security, privacy, and product managers. Engagements typically involve weeks to months of focused, high-stakes collaboration with business units to deliver production-ready AI solutions that drive measurable outcomes.Impact: The Senior Principal AI Forward Deployed Engineer plays a pivotal role in transforming AI prototypes into scalable, production-grade solutions that deliver quantifiable business value. By embedding directly with business units and taking full ownership of end-to-end delivery, this position significantly accelerates the organization's ability to realize returns on AI investments. The impact extends to driving operational efficiency gains, elevating guest experiences, and enabling data-driven decision-making through robust, deployed AI applications. This role serves as the critical bridge between technical capabilities and real-world business needs, ensuring AI initiatives advance beyond proof-of-concept to deliver innovation, competitive advantage, and tangible outcomes—including revenue growth, cost reduction, improved satisfaction scores, and new capabilities that were previously unattainable. The incumbent's contributions multiply across the organization as reusable patterns, best practices, and platform improvements benefit future deployments.Problem Solving: This role demands expert-level analytical and technical skills to address the most complex, ambiguous challenges in AI deployment and application development. The Senior Principal AI Forward Deployed Engineer must deconstruct vague business problems into actionable technical solutions by deeply understanding operational context, system constraints, data availability, and stakeholder priorities. Problem-solving involves conducting root cause analysis, architecting scalable and maintainable solutions, resolving critical production issues under pressure, and iterating approaches based on real-world feedback. The ability to navigate high-stakes trade-offs—speed vs. scalability, custom vs. reusable, perfect vs. good enough—is essential. The incumbent must also solve for complex real-world constraints including legacy system integration, shipboard connectivity limitations, distributed/offline environments, security requirements, and aggressive timelines while delivering solutions that meet rigorous technical standards and business objectives. This role serves as the escalation point for the most challenging technical blockers across AI deployments.Leadership: While this position does not have direct reports, it demonstrates senior-level leadership through technical ownership, strategic influence, and cross-functional impact. The Senior Principal AI Forward Deployed Engineer leads by owning end-to-end delivery of AI solutions, making critical architecture decisions, setting quality standards, and serving as a technical role model during engagements. By partnering with data scientists, engineers, and business stakeholders, the role builds alignment, removes blockers, and drives projects forward without formal authority. Leadership is further demonstrated through mentoring junior and mid-level engineers, establishing best practices and reusable patterns that scale across the organization, advocating for platform and tooling improvements based on field insights, and communicating effectively with executives on solution progress, technical trade-offs, and strategic recommendations. The incumbent champions responsible AI deployment influences the organization's AI roadmap through field-driven insights, and guides business units toward leveraging AI technologies effectively, ethically, and strategically.Requirements:Bachelor's degree in Computer Science, Software Engineering, Data Science or related fieldMaster's degree preferred but not requiredCertifications (required at least 1):AWS certifications (Solutions Architect, Developer Associate, Machine Learning Specialty)Kubernetes certifications (CKA, CKAD)Relevant AI/ML or cloud certificationsMinimum Experience:6-8+ years of software engineering experience with a focus on backend/full-stack development4+ years deploying AI/ML solutions in production environmentsLed/architected 3+ production AI systemsStrong hands-on experience with Docker, Kubernetes, and cloud-native architecturesExperience building and operating event-driven or streaming data systems (Kafka, Kinesis)Track record of delivering technical solutions in ambiguous, fast-moving environmentsTrack record leading technical engagements with senior/executive stakeholders.Mentored junior engineers; led cross-functional delivery teams.Preferred Experience:Experience in a Forward Deployed